Abstract

Fossil fuel is an important energy source, but is unavoidabiy running out. Since the cellulosic material is the most abundant source of organic matter, the ethanol, which is produced from cellulosic waste materials, is gaining more and more attention. These materials are cheap, renewable and their availability makes them superior compared to other raw materials. The cellulose must be hydrolyzed to glucose before it can be fermented to ethanol. The enzymatic hydrolysis of cellulose using cellulase enzymes is the most widely used method. The production cost of cellulase enzymes is the major cost in ethanol manufacture. To optimize the cost of ethanol production, enzyme stability needs to be improved through maintaining the activity of the enzymes and by optimizing the production of the cellulase. The aim of researchers, engineers and industrials is to get more biomass for the same cost. The filamentous fungus Trichoderma reesei has a long history in the production of the cellulase enzymes. This production can be influenced strongly by varying the growth media and culture conditions (pH, temperature, DO, agitation,... ). At present, it is my opinion that no modelling study has included both the hydrodynamic and kinetic aspects to investigate the effect of shear and mass transfer on the morphology of microorganisms that influence the rheology of the broth and production of cellulase. This thesis presents the development of a mathematical model for cellulase production and the growth of biomass in an airlift bioreactor. The kinetic model is coupled with the methodology of two-phase flow using mathematical models based on the bubble break-up and coalescence to predict mass transfer rate, which is one of the critical factor in the fermentation. A comparison between the results obtained by the developed model and the experimental data is given and discussed. The design proposed for the airlift geometry by Ahamed and Vermette enables us to get a high mass transfer and production rate. The results are very promising with respect to the potential of such a model for industrial use as a prediction tool, and even for design.